System identification method for Hammerstein processes

被引:63
|
作者
Sung, SW
机构
[1] Korea Adv Inst Sci & Technol, Dept Chem & Biomol Engn, Yuseong Gu, Taejon 305701, South Korea
[2] Korea Adv Inst Sci & Technol, Ctr Ultramicrochem Proc Syst, Yuseong Gu, Taejon 305701, South Korea
关键词
D O I
10.1021/ie0109206
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
A new strategy is proposed to identify Hammerstein-type nonlinear processes composed of a nonlinear static function and a linear dynamic. subsystem.; It completely separates, the identification problem of the linear. dynamic subsystem from that of the nonlinear static function using a special test signal. Then, quite useful, advantage over previous approaches ate guaranteed: we can use existing well-established linear system identification methods and their asymptotic properties of parameter estimates a,well as excellent techniques for minimal parametrization to identify the linear dynamic subsystem of the Hammerstein, process. Also, we can identify the nonlinear static function of the Hammerstein process analytically without any iterative optimization.
引用
收藏
页码:4295 / 4302
页数:8
相关论文
共 50 条
  • [1] Improved system identification method for Hammerstein-Wiener processes
    Sung, Su Whan
    Je, Cheol Ho
    Lee, Jietae
    Lee, Dong Hyun
    KOREAN JOURNAL OF CHEMICAL ENGINEERING, 2008, 25 (04) : 631 - 636
  • [2] Improved system identification method for Hammerstein-Wiener processes
    Su Whan Sung
    Cheol Ho Je
    Jietae Lee
    Dong Hyun Lee
    Korean Journal of Chemical Engineering, 2008, 25 : 631 - 636
  • [3] Nuclear Norm Subspace Identification Method for Hammerstein System Identification
    Dai, Mingxiang
    Zhang, Jingxin
    He, Ying
    Yang, Xinmin
    2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2014, : 2334 - 2339
  • [4] Recursive Identification Method for Hammerstein-Wiener System
    Yang, Xiaolong
    Fang, Hai-tao
    2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 1945 - 1950
  • [5] A noniterative neuro-fuzzy based identification method for Hammerstein processes
    Jia, L
    Chiu, MS
    Ge, SZS
    JOURNAL OF PROCESS CONTROL, 2005, 15 (07) : 749 - 761
  • [6] Recursive maximum likelihood method for the identification of Hammerstein ARMAX system
    Ma, Liang
    Liu, Xinggao
    APPLIED MATHEMATICAL MODELLING, 2016, 40 (13-14) : 6523 - 6535
  • [7] On a Method of Identification of the Nonlinear Static Characteristic of a Hammerstein System.
    Niedzwiecki, Maciej
    Archiwum Automatyki i Telemechaniki, 1980, 25 (01): : 51 - 62
  • [8] A nonlinear recursive instrumental variables identification method of Hammerstein ARMAX system
    Ma, Liang
    Liu, Xinggao
    NONLINEAR DYNAMICS, 2015, 79 (02) : 1601 - 1613
  • [9] A nonlinear recursive instrumental variables identification method of Hammerstein ARMAX system
    Liang Ma
    Xinggao Liu
    Nonlinear Dynamics, 2015, 79 : 1601 - 1613
  • [10] CONTROLLER-DESIGN ORIENTED MODEL IDENTIFICATION METHOD FOR HAMMERSTEIN SYSTEM
    LANG, ZQ
    AUTOMATICA, 1993, 29 (03) : 767 - 771